1. Field of the Invention
The present invention is generally related to a means for characterizing the operation of an apparatus and prognosticating a condition of an apparatus and, more particularly, to a method by which a marine propulsion system can be monitored in order to both diagnose its current operating condition and to predict future failures before they become catastrophic.
2. Description of the Prior Art
In any complex system or apparatus, it is often desirable to monitor certain parameters to determine if the apparatus is operating in a proper manner. For example, in an automobile, oil pressure and coolant temperature are monitored continually. If oil pressure drops below a predetermined threshold magnitude, an alarm signal is provided to inform the operator that low oil pressure exists and continued operation of the automobile under these conditions could be severely damaging to the engine. Similarly, coolant temperature is monitored and compared to a predetermined threshold magnitude. When the coolant temperature exceeds the predetermined threshold, an alarm signal is provided to the operator of the automobile that continued operation under the overheated conditions could result in severe damage to the engine. These operating conditions are relatively straightforward and easily monitored. In both examples, the alarm signal represents a present situation that requires immediate attention. In other words, the overtemperature alarm does not indicate that a potential future overtemperature condition may occur but, instead, it indicates that the coolant temperature is presently greater than the predetermined temperature threshold. Similarly, the low pressure alarm does not predict a low pressure in the future but, instead, represents an existing condition in which the oil pressure is currently lower than required for proper operation of the engine.
Many techniques have been developed to monitor operating equipment and predict future failures that are not readily apparent and not easily detectable by basic monitoring techniques.
U.S. Pat. No. 5,633,456, which issued to Stander on May 27, 1997, describes an engine misfire detection system with digital filtering. The apparatus and method provide for detecting cylinder misfires in an internal combustion engine of a motor vehicle by digitally filtering out noise related signals to improve the signal to noise ratio. Crankshaft rotation is sensed and crankshaft velocities are measured for each cylinder. Changes in angular velocity are determined and correspond to each of a plurality of cylinder firing events. A window of consecutive changes in angular velocity are used with a digital filter. The digital filter contains filter coefficients which are determined from a frequency analysis for a given engine by distinguishing between actual misfire events and noise related event frequencies. From the analysis, a cut off frequency between actual misfires and noise is determined which is then used to determine the filter coefficients. The digital filter generates a filter output for the current cylinder firing event and the filter output is preferably multiplied by a gain to provide to provide a compensated filter output. The compensated filter output is compared to a threshold value and a misfire event is determined for the selected cylinder based on the comparison. A high pass filter may be employed to filter out low frequency noise related signals such as those associated with a power train bobble. Similarly, a low pass filter can be used to filter out high frequency noise signals such as those associated with crankshaft torsional vibrations. Both high and low pass filters could be employed in the alternative by using a high pass filter at low engine speeds and a low pass at high engine speeds.
U.S. Pat. No. 5,745,382, which issued to Vilim et al on Apr. 28, 1998, describes a neural network based system for equipment surveillance. The method and system is provided for performing surveillance of transient signals of an industrial device to ascertain the operating state. The method and system involves the steps of reading into a memory training data and determining neural network weighting values until achieving target outputs close to the neural network output. If the targets outputs are inadequate, wavelet parameters are determined to yield neural network outputs close to the desired set of target outputs and then providing signals characteristic of an industrial process and comparing the neural network output to the industrial process signals to evaluate the operating state of the industrial process.
U.S. Pat. No. 5,852,793, which issued to Board et al on Dec. 22, 1998, describes a method and apparatus for predictive diagnosis of moving machine parts. It is intended for automatically predicting machine failure and comprises a transducer sensor, such as piezoelectric crystal, and is applied to a machine for sensing machine motion and structure-borne sound, including vibration friction, and shock waves. The structure-borne sound and motion sensed is converted to electrical signals which are filtered to leave only the friction and shock waves, which waves are processed, as by detecting the envelope and integrating beneath the envelope, resulting in a measure of friction and shock wave energy. This measure is computed and processed for producing fault progression displays for periodic and aperiodic damage. This is accomplished in a personal computer, menu-driven environment.
U.S. Pat. No. 5,646,340, which issued to Gee et al on Jul. 8, 1997, describes an analytical tachometer. The method and apparatus for engine and rotary machine analysis provides a vibration sensor adapted to produce a plurality of superimposed waveforms corresponding to engine or machine operating parameters including rotational speed. The signals are transmitted by an RF transmitter/receiver system in analog modulated form to a data capture and analytical function unit utilizing a software sub-system in which a power spectral density plot is produced containing a signature characteristic of the engine or other machine under test. This signature is recognized by a signature detect algorithm which can recognize and trace the signature across the frequency spectrum covered by the apparatus so as to provide a continuous tachometric function not requiring lo the filtering out or other removal of irrelevant data. A diagnostic function arises from detection of the presence of additional harmonic peaks within the signature. A capacitive coupling offers a simplified tachometric function based upon low voltage signals in the injector leads of a spark ignition engine.
The patents described above are hereby explicitly incorporated by reference in the present application.
In the second edition of "RANDOM DATA, ANALYSIS AND MEASUREMENT PROCEDURES" by Bendat and Piersol, published by John Wiley & Sons, paragraph 6.1.2 describes ordinary coherence functions in relation to power spectral densities. In addition, it describes an example of an application of a power spectral density with regard to an airplane flying through atmospheric turbulence. The application of power spectral density profiles and the integrals thereof are generally known to those skilled in the art. Coherence functions can be used to distinguish between a reference power spectral density profile and a current power spectral density profile to determine whether or not the differences between the two are normal variations or, alternatively, represent an actual difference between the two profiles.
In certain mechanical apparatus, it would be significantly beneficial if a means could be provided that would allow the prognostication of faults before the faults become catastrophic or disabling. This is especially true in marine propulsion systems. If a system could be provided that predicted failure of mechanical or electrical components before those failures actually occurred, the problem components could be repaired or replaced and the failure of the components would not result in the marine vessel operator being stranded and unable to return to port. If an automobile engine fails, the driver is usually able to obtain alternative means of transportation that would allow the operator to return home safely and repair the automobile at some future time. In marine propulsion system applications, it is often the case that the marine vessel can be far from either the nearest convenient port or other vessels when an engine failure or other mechanical failure occurs. If the failure occurs when the marine vessel is far from land, alternative means for the operator to return to port may not be readily available. It would therefore be significantly beneficial if failures could be predicted sufficiently before their actual occurrences to allow the marine vessel operator to correct the problem before it occurs.